Platform capaBIlity · reporting · BI dashboard · data lake
Reporting, SQL Explorer & Data Lake
Turn operational lab execution into queryable reports,
custom analytical datasets, exports, and BI-ready data products.
Flask Track comBInes system reports, a SQL explorer, a visual query builder,
custom protocol form data, and exportable report results in one reporting layer built for BIological
operations.
Reporting built on real operational data
Flask Track reporting is grounded in the records your lab already creates:
protocols, workflow steps, batches, samples, catalog items, compliance events,
audit records, supplier data, files, and custom protocol form submissions.
📊
System Reports
Use built-in reports for operational records:
batches, samples, protocols, events, catalogs, compliance, audit, and procurement.
🧮
SQL Explorer
Query live structured records, preview schemas,
filter data, join operational tables, and build reusable report queries.
🧱
Visual Query Builder
Build reports through a guided interface when users need
structured filtering and joins without writing every query by hand.
🔎
Grid Visualizer
Inspect result sets in a tabular grid before saving,
exporting, sharing, or calling reports through the API.
💾
Saved Reports
Save, edit, reuse, and share report definitions for
recurring operational review, compliance, procurement, and analytics.
Share your reports across the organization and allow others to easily discover them in the reporting
dashboard.
📤
Exports & Report Outputs
Export report results as CSV, JSON, HTML, or Parquet
for analysis, review, archiving, and downstream systems.
Custom protocol data becomes queryable automatically
Protocol steps can define custom data forms for the exact measurements,
observations, quality checks, or process variables your lab needs.
Flask Track stores that submitted data in an indexed, queryable analytical bucket
so custom reports can join it back to core operational records.
📝
Custom Step Forms
Define structured data capture for protocol steps:
measurements, observations, QC fields, decisions, and process-specific values.
🪣
Automatic Data Buckets
Store custom form submissions in automatically created,
indexed data buckets designed for reporting and downstream analysis.
🔗
Join Custom Data to Core Tables
Query custom form data alongside samples, batches,
protocols, workflow steps, catalog items, users, and events.
📈
Custom Operational Analytics
Build reports around the values your lab actually captures,
not just generic system fields. Defining custom forms for protocol step completions allows endless
data and schema
customizations, this allows you to seamlessly capture that data in a reportable fashion for your
users and systems APIs to ingest all in one place.
Data lake powered for scale
Flask Track combines live operational tables with historical analytical
data, giving teams a reporting layer that can
grow beyond basic application dashboards.
🐘
Live Tables
Query core application records for protocols, users,
samples, workflows, catalogs, compliance, audit, and execution history.
🪄
AI Assisted SQL generation
When creating reports you can rely on your AI assistant armed with knowledge of the reporting data
schemas and
will help you build a custom report without being someone who lives in SQL day in and day out.
🗄️
Analytical Storage
Store custom datasets, report outputs, and analytical records
in dedicated object storage for scalable access and retention.
🧩
Unified Query Layer
Join live operational tables with custom analytical buckets
so reports can reflect both standard and protocol-specific data.
Reports that can be saved, shared, exported, and executed
Reports are not one-off downloads. Flask Track lets teams maintain reusable
report definitions that support dashboards, audits, procurement reviews,
custom analysis, and external data access.
💾
Save & Edit Reports
Create report definitions once, revise them over time,
and reuse them for recurring operational or compliance review.
🤝
Share Reports
Share approved reports with the organization to allow all team users to view the final results
🔌
Report API Access
Run saved reports over the API and retrieve results as
JSON, CSV, Parquet, or HTML for dashboards, services, and external automation pipelines.
🧾
Compliance & Review Outputs
Produce evidence packets, operational summaries,
exception reviews, audit extracts, and structured report archives.
Track audits and their results for historical reference and review.
Useful reporting across the entire lab operation
🔁
Workflow & Execution Reports
Analyze protocol usage, step completion, batch progress,
sample events, state transitions, outcomes, files, and measurements.
🛡️
Compliance Reports
Track regulatory surfaces, framework rules, approvals,
incidents, evidence, restricted actions, and review history.
⛓️
Audit Reports
Export actor attribution, request context, affected records,
timestamps, before/after snapshots, and integrity status.
Built for labs to enjoy the scaleability and historical data of traditional BI systems, review, exports, and
downstream analytics
- ✔ Built-in system reports backed by structured Postgres operational data
- ✔ SQL editor, visual query builder, schema preview, result grid, and reusable report definitions
- ✔ Custom protocol step forms that create indexed, queryable analytical buckets
- ✔ Joins across custom form data, workflows, samples, batches, protocols, users, and catalogs
- ✔ Data lake access powered by Apache Arrow Flight, S3-backed storage, and live Postgres tables
- ✔ Save, edit, share, export, and execute reports through the reporting interface
- ✔ Retrieve saved report results through the API as JSON or Parquet
From lab execution to analytical infrastructure
Flask Track reporting turns daily lab activity into a flexible analytical layer.
Standard operational records and lab-specific custom form data can be queried together,
visualized in a BI dashboard, exported for review, and accessed programmatically when
teams need reporting beyond the application UI.